Data storage resource allocation using blacklisting of data storage requests classified in the same category as a data storage request that is determined to fail if attempted

ABSTRACT

A resource allocation system begins with an ordered plan for matching requests to resources that is sorted by priority. The resource allocation system optimizes the plan by determining those requests in the plan that will fail if performed. The resource allocation system removes or defers the determined requests. In addition, when a request that is performed fails, the resource allocation system may remove requests that require similar resources from the plan. Moreover, when resources are released by a request, the resource allocation system may place the resources in a temporary holding area until the resource allocation returns to the top of the ordered plan so that lower priority requests that are lower in the plan do not take resources that are needed by waiting higher priority requests higher in the plan.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a Continuation of U.S. patent application Ser. No.14/804,446, entitled “DATA STORAGE RESOURCE ALLOCATION USINGBLACKLISTING OF DATA STORAGE REQUESTS CLASSIFIED IN THE SAME CATEGORY ASA DATA STORAGE REQUEST THAT IS DETERMINED TO FAIL IF ATTEMPTED,” filedon Jul. 21, 2015, which is a Divisional of U.S. patent application Ser.No. 12/142,423, entitled “DATA STORAGE RESOURCE ALLOCATION BY PERFORMINGABBREVIATED RESOURCE CHECKS BASED ON RELATIVE CHANCES OF FAILURE OF THEDATA STORAGE RESOURCES TO DETERMINE WHETHER DATA STORAGE REQUESTS WOULDFAIL,” filed on Jun. 19, 2008, and which are hereby incorporated byreference in their entireties herein.

BACKGROUND

Systems used to perform data storage operations of electronic data aregrowing in complexity. However, current systems may not be able toaccommodate increased data storage demands or efficient and timelyrestore operations. Often, these systems are required to store largeamounts of data (e.g. all of a company's data files) during a timeperiod known as a “storage window.” The storage window defines aduration and actual time period when the system may perform storageoperations. For example, a storage window may be for twelve hours,between 6 PM and 6 AM (that is, twelve non-business hours). Often,storage windows are rigid and unable to be modified. Therefore, whendata storage systems attempt to store increasing data loads, they mayneed to do so without increasing the time in which they operate.Additionally, many systems perform daily stores, which may add furtherreliance on completing storage operations during allotted storagewindows.

Moreover, each data storage operation requires multiple resources, suchas access to a tape drive, allocation of a stream for that tape drive,an available tape on which to store data, a media agent computer toprocess and monitor the request, and so forth. Given multiple datastorage requests and multiple resources, with each request requiringdifferent resources for different periods of time, optimizing allocationof these resources can be a very complex operation as the number ofrequests and resources grow. Processor time can grow exponentially asthe requests and resources grow.

Multidimensional resource allocation is an inherently complex problem tosolve. As noted above, a number of disparate resources need to beavailable to satisfy a single request, such as available media, acompatible drive from a pool of drives, etc. Also, additionalconstraints must be satisfied, such as a load factor on a computerwriting the data, a number of allowed agents or writers to a targetmedia (e.g., disk or tape), etc.

Rules of resource allocation further complicate the problem. Forexample, rules may be established regarding failover such that when agiven drive fails, the system can substitute in another drive. Likewise,rules may be established for load balancing so as not to overtax a givendrive, but to spread the burden over a pool of drives. If a primaryresource candidate is not available, then the system may allocateresources from an alternate resource pool, which may or may not besatisfactory. Time delay factors arise when alternatives are considered.

Furthermore, resource requests arrive in a random order; however, eachincoming request has either a pre-assigned or dynamically changingpriority. Furthermore, resources are freed up in a random order and maybe associated with lower priority requests. A multiple set matchingalgorithm is not possible in such a complex environment.

In order to make a best match, a sorted list of requests is oftenmaintained. This queue of requests is then walked and resourcesallocated to higher priority requests first before lower priorityrequests can be honored. The matching process for each request is verytime consuming given the number of resources that must be made availablefor each job.

Prior systems have attempted to ameliorate these problems by reducingthe number of variables and thereby reducing the complexity of suchoptimizations of resource allocations. Other systems have employeddedicated resources, often for higher priority requests. However, whenthose resources become freed up, they sit idle until other requestsdedicated to those resources arrive. Other systems have solved thiscomplexity problem by simply reducing the number of requests andcreating smaller units of resources. This fragments a system, and can beinefficient.

Requests in a data management system often ultimately fail. For example,a required resource may be down or in short supply. Unfortunately, thedata management system has often committed significant resources in theresource allocation process before the request fails. For example, thedata management system may spend precious time gathering other resourcesor data only to discover that the tape drive to which the data should becopied is not available. This causes the data management system to wastetime that reduces the amount of productive work that the system canperform during the storage window.

The foregoing examples of some existing limitations are intended to beillustrative and not exclusive. Other limitations will become apparentto those of skill in the art upon a reading of the Detailed Descriptionbelow. These and other problems exist with respect to data storagemanagement systems.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A is a block diagram illustrating an example of components used indata storage operations.

FIG. 1B is a block diagram illustrating an alternative example ofcomponents used in data storage operations.

FIG. 1C is a block diagram illustrating an alternative example ofcomponents used in data storage operations.

FIG. 2 is a block diagram illustrating an example of a data storagesystem.

FIG. 3 is a block diagram illustrating an example of components of aserver used in data storage operations.

FIG. 4 is a flow diagram illustrating an example optimize requestsroutine.

FIG. 5 is a flow diagram illustrating an example handle requestsroutine.

FIG. 6 is a flow diagram illustrating an example build grid routine.

FIG. 7 is a block diagram illustrating an example environment in which agrid store may be applied.

In the drawings, the same reference numbers and acronyms identifyelements or acts with the same or similar functionality for ease ofunderstanding and convenience. To easily identify the discussion of anyparticular element or act, the most significant digit or digits in areference number refer to the Figure number in which that element isfirst introduced (e.g., element 420 is first introduced and discussedwith respect to FIG. 4).

The headings provided herein are for convenience only and do notnecessarily effect the scope or meaning of the claimed invention.

DETAILED DESCRIPTION

Described in detail herein is a resource allocation system that mayemploy one or more resource optimization subsystems or routines, whichmay be used individually or collectively to provide resource allocationin a data storage management environment. The system helps matchresources in a multidimensional data storage management environment in amore efficient fashion, which permits highly scalable systems. Assystems grow, a queue of jobs grows. For example, a queue may includethousands of data storage jobs, where each job is associated withmultiple resource requests. Improving the allocation of resourcesenables more jobs to be performed within a particular time window, suchas overnight or during off-peak hours for a business.

In some embodiments, the resource allocation system begins with anordered plan for matching requests to resources that is sorted bypriority. The initial priority scheme may be determined in a variety ofways. For example, an administrator may determine which items are mostimportant and give those items a higher priority. As another example,the system may prioritize requests according to geographic or networkrouting, such as by establishing a preference for satisfying a requestwith the closest computer to a computer holding data for a request. Theresource allocation system attempts to respect the input priority, andwill prefer to complete higher priority requests before lower priorityrequests. The initial ordered plan forms a starting point that thesystem can refine by each of the methods described herein.

The resource allocation system uses three primary methods for matchingresources to requests that are described in further detail in thefollowing sections: Preordered/Intelligent Resource Checks, CategoryBlacklisting, and Resource Holding Area. The Dynamic Routing/Allocationsection below describes additional techniques for matching requests toresources.

One resource optimization routine employs abbreviated pre-orderedmatching where only a subset of resources are checked in a pre-orderedfashion. For example, physical resources such as drives are in shortsupply so checks of these resources are quick given their small numbers,and their tendency to more frequently fail. Thus, physical checks aredone first, then logical checks performed later, so that when a physicalresource fails, it saves the system time it may have spent checkinglonger lists of logical resources. If a request fails based on a checkof this shortened list, then the system moves to the next request in aqueue.

As the requests for individual resources grow into the thousands or tensof thousands, and the number of resources grows to the hundreds, even anabbreviated matching list can consume considerable processing cycles.Therefore, a second resource optimization routine, categoryblacklisting, provides further efficiencies and scale to a queue ofpotentially thousands of jobs with their associated resource requests byassigning requests with a category code, such as a storage policy. Allresource requests having the same category code are associated with thesame set of resource requests and rules that govern how to allocatethose resources. Once a request is denied, the entire category isblacklisted or otherwise excluded from future resource allocationrequests. Thus, subsequent requests in the same category may not evenmatched or analyzed by the system based on a blacklisting flagassociated with that request.

A third resource optimization routine employs a temporary holding areafor released resources to preserve priorities. Since resources arereleased back into a pool of available resources at random times, theproblem arises that a request having a lower priority will receive thatresource ahead of a request having a higher priority. To overcome thisshortcoming, released resources are held in a temporary holding area.When the resource allocation system loops back to the top of the queue(i.e., to those unfulfilled requests having the highest priority), thenewly available resources from the temporary holding area are added backto the general pool of available resources. This helps insure thatrequests having higher priority will have access to any releasedresources before lower priority requests.

Various examples of the system will now be described. The followingdescription provides specific details for a thorough understanding andenabling description of these examples. One skilled in the art willunderstand, however, that the system may be practiced without many ofthese details. Additionally, some well-known structures or functions maynot be shown or described in detail, so as to avoid unnecessarilyobscuring the relevant description of the various examples.

The terminology used in the description presented below is intended tobe interpreted in its broadest reasonable manner, even though it isbeing used in conjunction with a detailed description of certainspecific examples of the system. Certain terms may even be emphasizedbelow; however, any terminology intended to be interpreted in anyrestricted manner will be overtly and specifically defined as such inthis Detailed Description section.

Suitable System

Referring to FIG. 1A, a block diagram illustrating components of a datastream is shown. The stream 110 may include a client 111, a media agent112, and a secondary storage device 113. For example, in storageoperations, the system may store, receive and/or prepare data to bestored, copied or backed up at a server or client 111. The system maythen transfer the data to be stored to media agent 112, which may thenrefer to storage policies, schedule policies, and/retention policies(and other policies), and then choose a secondary storage device 113 forstorage of the data. Secondary storage devices may be magnetic tapes,optical disks, USB and other similar media, disk and tape drives, and soon.

Referring to FIG. 1B, a block diagram illustrating components ofmultiple selectable data streams is shown. Client 111 and any one ofmultiple media agents 112 may form a stream 110. For example, one streammay contain client 111, media agent 121, and storage device 131, while asecond stream may use media agent 125, storage device 133, and the sameclient 111. Additionally, media agents may contain additional subpaths123, 124 that may increase the number of possible streams for client111. Examples of subpaths 123, 124 include host bus adapter (HBA) cards,Fibre Channel cards, SCSI cards, and so on. Thus, the system is able tostream data from client 111 to multiple secondary storage devices 113via multiple media agents 112 using multiple streams.

Referring to FIG. 1C, a block diagram illustrating components ofalternative multiple selectable data streams is shown. In this example,the system may transfer data from multiple media agents 151, 152 to thesame storage device 113. For example, one stream may be from client 141,to media agent 151, to secondary storage device 113, and a second streammay be from client 142, to media agent 152, to secondary storage device113. Thus, the system is able to copy data to one secondary storagedevice 113 using multiple streams 110.

Additionally, the system may stream may be from one client to two mediaagents and to one storage device. Of course, the system may employ otherconfigurations of stream components not shown in the Figures.

Referring to FIG. 2, a block diagram illustrating an example of a datastorage system 200 is shown. Data storage systems may contain some orall of the following components, depending on the needs of the system.

For example, the data storage system 200 contains a storage manager 210,one or more clients 111, one or more media agents 112, and one or morestorage devices 113. Storage manager 210 controls media agents 112,which may be responsible for transferring data to storage devices 113.Storage manager 210 includes a jobs agent 211, a management agent 212, adatabase 213, and/or an interface module 214. Storage manager 210communicates with client(s) 111. One or more clients 111 may access datato be stored by the system from database 222 via a data agent 221. Thesystem uses media agents 112, which contain databases 231, to transferand store data into storage devices 113. Client databases 222 maycontain data files and other information, while media agent databases231 may contain indices and other data structures that assist andimplement the storage of data into secondary storage devices, forexample.

The data storage system may include software and/or hardware componentsand modules used in data storage operations. The components may bestorage resources that function to copy data during storage operations.The components may perform other storage operations (or storagemanagement operations) other than operations used in data stores. Forexample, some resources may create, store, retrieve, and/or migrateprimary or secondary data copies. The data copies may include snapshotcopies, backup copies, HSM copies, archive copies, and so on. Theresources may also perform storage management functions that maycommunicate information to higher level components, such as globalmanagement resources.

In some examples, the system performs storage operations based onstorage policies, as mentioned above. For example, a storage policyincludes a set of preferences or other criteria to be considered duringstorage operations. The storage policy may determine or define a storagelocation and/or set preferences about how the system transfers data tothe location and what processes the system performs on the data before,during, or after the data transfer. Storage policies may be stored instorage manager 210, or may be stored in other resources, such as aglobal manager, a media agent, and so on. Further details regardingstorage management and resources for storage management will now bediscussed.

Referring to FIG. 3, a block diagram illustrating an example ofcomponents of a server used in data storage operations is shown. Aserver, such as storage manager 210, may communicate with clients 111 todetermine data to be copied to primary or secondary storage. Asdescribed above, the storage manager 210 may contain a jobs agent 211, amanagement agent 212, a database 213, and/or an interface module 214.Jobs agent 211 may manage and control the scheduling of jobs (such ascopying data files) from clients 111 to media agents 112. Managementagent 212 may control the overall functionality and processes of thedata storage system, or may communicate with global managers. Database213 or another data structure may store storage policies, schedulepolicies, retention policies, or other information, such as historicalstorage statistics, storage trend statistics, and so on. Interfacemodule 214 may interact with a user interface, enabling the system topresent information to administrators and receive feedback or otherinput from the administrators or with other components of the system(such as via APIs).

The server 300 contains various components of the resource allocationsystem such as a receive requests component 310, an optimize requestscomponent 320, a handle requests component 330, a request storecomponent 340, a resource store component 350, and a build gridcomponent 360. The receive requests component 310 provides input to theresource allocation system in the form of an initial priority orderedplan (e.g., a list or queue) that specifies requests to be performed bythe system. The optimize requests component 320 modifies the initialplan by performing one or more optimization routines on the initialplan. For example, the resource allocation system may performabbreviated checks to remove requests from the initial plan that wouldfail. The handle requests component 330 dispatches, performs or at leastinitializes each request and performs other optimizations based on theresult of each request. For example, when a request fails, the handlerequests component 330 may remove similar requests from the plan, suchas by blacklisting categories of requests. The request store component340 stores the request plan and supplemental information about eachrequest, such as any associated storage policy or metadata. The resourcestore component 350 stores information about the resources availablethroughout the system, such as drives, networks, media, and so forth.The build grid component 360 builds a grid of resources and requests bysubdividing resources and requests according to certain criteria, suchas geographic location of resources. These components and theiroperation are described in further detail herein.

Storage operations cells may by organized in a hierarchical fashion toperform various storage operations within a network. Further details onsuch a hierarchical architecture may be found in U.S. patent applicationSer. No. 11/120,662, entitled Hierarchical Systems and Methods forProviding a Unified View of Storage Information, filed May 2, 2005(attorney document no. 60692.8019), which is hereby incorporated hereinby reference.

Preordered/Intelligent Resource Checks

The resource allocation system or process matches pending requests toresources by performing abbreviated checks to determine if a requestwould succeed. If a check fails, then the resource allocation system canmove on to the next request, having spent less time than if the systembegan performing the data storage operation specified by the request infull (e.g., not abbreviated) and the data storage operation failed. Theresource allocation system performs the abbreviated checks in apreordered fashion. For example, physical checks (e.g., determiningwhether the necessary hardware is working) may be performed beforelogical checks (e.g., determining whether a device is in use). Anunderlying goal is to check requests that have the highest chance offailure to remove them from the plan first. In addition, since manyrequests have dependent requests, when the resource allocation systemcan eliminate a request from the plan, it can also remove each of therequest's dependent requests. Requests that fail the checks would havefailed anyway, so determining that before resources have been committedand time has been wasted allows the system to spend more time working onrequests that are more likely to succeed.

In one example, since physical resources are often the most difficult toacquire or fulfill, the matching routine may analyze a current job in aqueue and first recognize that one resource being requested is a tapedrive. Typically, physical resources like disks or tape drives are inshort supply. The matching routine may perform a physical check to seewhether that physical resource (tape drive) is offline or malfunctioning(a physical check) before doing a logical check of that resource (e.g.,whether it is busy with another job). Likewise, the matching process maylook at the state of the network to determine whether a path or streamis possible to satisfy a currently analyzed job. Physical checks areoften faster than logical checks as they operate on a smaller list ofavailable resources and tend to fail more often. When a physical checkfails, the resource allocation system saves time that might have beenwasted if a longer logical check had been performed first.

The following is an example of physical checks that may be performed bythe resource allocation system in the following order:

-   1) availability of drives (e.g., tape, optical, or magnetic),-   2) availability of device streams that can be used on the storage    policy,-   3) availability of a tape library, availability of a media agent,-   4) availability of a host bus adapter card, number of drives that    can be used in parallel from a tape library (e.g., a drive    allocation policy for a library),-   5) number of drives that can be used on a single media agent at a    given time (e.g., a drive allocation policy for a drive pool),-   6) availability of tapes or other media, and so forth.

The resource allocation system next performs logical checks. Forexample, the system may determine whether a tape drive is busy orflagged do not use. Some devices may be reserved for other purposesoutside of the resource allocation system such as an administratorindicating that the resource allocation system should not schedulerequests to use those devices.

In some embodiments, the resource allocation system compares only asubset of resource requests for that job to available resources todetermine whether that job can be satisfied. A resource allocationsystem or process may include an abbreviated pre-order matching routinethat identifies a subset of resource requests and performs a matching orallocation based on only that subset, rather than the entire set ofresources. Notably, if the matching routine determines, based on anordered review of a subset of resource requests in a given job, thatthat job cannot be satisfied, then the matching routine may stop anyfurther matching operations for that job and simply move to the next jobin the queue. This saves valuable resources in determining how tooptimize each job (with its associated resource requests) in the queue.Rather than try to satisfy requests, the matching routine looks toeliminate jobs that request resources that cannot currently besatisfied.

Thus, the matching routine in one example reviews each incoming job inthe queue, in order, and determines whether that job can be skipped,ignored or excluded during a current cycle through the queue. Thematching routine compares the various resource requests in the job tothe resources above to see whether that current job can be ignored. Forexample, a current job analyzed by the matching routine may request thefollowing resources: an available tape drive, a device stream for astorage policy, access to a tape library, a particular media agent, andan available tape. The matching routine first determines whether a tapedrive is physically available, and if so, determines whether a devicestream to that tape drive for the storage policy is available. If not,then the matching routine does not look to determine whether any otherresources in the job are available, but simply moves to the next job inthe queue.

FIG. 4 is a flow diagram that illustrates the processing of the optimizerequests component 320, in one embodiment. The optimize requestscomponent 320 is invoked when the resource allocation system receives aninitial plan containing a prioritized list of data storage requests. Theplan may come from a variety of sources. For example, an administratormay create the initial plan that is composed of each of the storagerequests that the administrator wants a data storage system to perform.As another example, each computer in an organization may automaticallyregister a nightly request to archive files or perform other datastorage operations, and a data storage system may collect the requests.In block 410, the component receives the initial list of requests. Thelist of requests is in priority or other order, based on requirements ofthe data storage system for completing the requests. For example, anadministrator may order requests based on the importance that eachrequest be completed. In block 420, the component performs theabbreviated checks described above. For example, the component mayperform a series of physical checks for each request followed by aseries of logical checks (and the checks may only check a subset of theresources required by the request). When a request fails a particularcheck, the request is removed from the list or marked as not to beperformed. In block 430, the component handles each request in turn bytraversing the list as described in further detail with respect to FIG.5.

Under the abbreviated or preordered/intelligent check of resources, thesystem performs one or more abbreviated checks by performing a selectedsubset of one or more checks for whether one or more selected datastorage resources are available to satisfy a data storage request. Asnoted above, the selected one data storage resource may be a physicaldata storage resource, rather than a logical data storage resource. Whenthe one or more abbreviated checks indicate that the data storagerequest would fail if performed, then the system updates the list ofdata storage requests to indicate that that data storage request shouldnot be performed, without attempting to perform that data storagerequest and without performing a check of all data storage resourcesrequired for performing that data storage request. Thereafter, thesystem again performs one or more abbreviated checks on the next datastorage request in the list of data storage requests, and updates thelist when the newly performed abbreviated checks indicate that this nextdata storage request would fail if performed.

When the abbreviated pre-ordered checks are complete, the resourceallocation system will have reduced the initial ordered plan by removingrequests from the plan that would eventually fail if allowed tocontinue. The number of requests removed can be significant, leading tosignificant time savings and more time for the resource allocationsystem to spend on requests that will likely succeed.

Category Blacklisting

The second method the resource allocation system uses for matchingresources to requests is called category blacklisting. As the requestcount and number of resources grow, even the abbreviated checksdescribed above may take a long time. Category blacklisting attempts tomake the process of matching resources to requests more efficient sothat the system scales further. This process is described in furtherdetail with reference to FIG. 5.

In some embodiments, each request has a category code. For example, thecategory code may be associated with a storage policy. All requests inthe same category have similar resource requirements and rules governinghow to allocate the resources. When the resource allocation systemdenies a request, either during abbreviated checking or by actuallyattempting to perform the request and reaching a point of failure, thenthe resource allocation system blacklists the entire category. If onerequest in the category fails then all of the requests in the categoryare likely to fail. By removing these other requests, the resourceallocation system prevents wasting time on failed requests and has moretime available to perform requests that will likely succeed.

In some embodiments, the resource allocation system determines alikeness factor that indicates a degree of similarity between requestsassigned to a particular category. If the resource allocation systemdenies a request, then the resource allocation system removes otherrequests that have a high enough likeness factor from the plan. Thelikeness factor considers a subset of resources that the request needs,and may separate the resources into common and unique subsets. Theresource allocation system may take two or three of the most commonresources to compose the likeness factor. If a request is denied for acommon resource, then the resource allocation system blacklists thecategory. However, if the request is denied based on a unique resource,then it is less likely that the entire category will suffer the samefailure, and the resource allocation system may not blacklist thecategory.

When the category blacklisting process is complete, the resourceallocation system will have further reduced the ordered plan by removingrequests from the plan that would eventually fail if allowed tocontinue. The number of requests removed can be significant, leading tosignificant time savings and more time for the resource allocationsystem to spend on requests that will likely succeed.

Resource Holding Area

To preserve priorities in the job queue, the resource allocation systemmay employ a temporary holding area for released resources. As jobs arecompleted, resources are freed up to be available for subsequent jobrequests. However, as noted above, the freed up resources could beprovided to lower priority jobs. Therefore, when resources are freed up,the resource allocation system places them into a logical holding area.They remain in the holding area until the resource allocation system haswalked the queue and returns to the top of the queue. At that point, theresource allocation system starts afresh and may satisfy highestpriority job requests with all available resources, including those thathad been freed up while walking the queue and placed temporarily in theholding area.

In general, the resource allocation system operates in a loop repeatedlytraversing the ordered plan of requests and initiating each request inturn as the resources required by the request are available. When theend of the plan is reached, the system starts again from the top.However, a problem arises when a request with lower priority attempts tograb a resource ahead of a request with higher priority. This can happenas the system is traversing the plan when a particular request completesthat releases resources that caused a request earlier in the plan to bepostponed. Thus, when resources are released by a request, the resourceallocation system may place these resources into a temporary resourceholding area so that they are not yet available to subsequent requestsin the plan. When the resource allocation loop returns to the top of theplan, the resource allocation system makes these resources available toall requests. This ensures that requests with highest priority will haveaccess to any released resources first.

In some embodiments, the resource allocation system receivesconfiguration information from an administrator that alters the behaviorof the resource holding area. For example, the configuration informationmay indicate that the resource holding area is not used until theresource allocation system is at a certain depth in the plan or queue.As an example, if the resource allocation system is at the third requestin the plan and the second request released a resource that the thirdrequest needs, then the resource allocation system may go ahead and givethe resource to the third request rather than waiting until the entireplan has been traversed. It is less likely that any of the prior higherpriority requests in the plan need the resource or the resource may beavailable again by the time the resource allocation system has traversedthe entire plan.

The resource allocation system may include an administrator interface(not shown) that allows a system administrator to configure the holdingarea. For example, if a resource is freed up while the system isanalyzing the first quarter or tenth of the queue, then it may beimmediately placed back into the pool of available resources, ratherthan waiting for the entire queue to be walked. As another example, ifthe resource allocation system is currently analyzing the third requestin the queue, and that third request may be satisfied with a resource inthe temporary holding area, then the system may allocate that resourcefrom the temporary holding area. Alternatively or additionally, the userinterface may permit the system administrator to otherwise allow aresource from the temporary holding area to be placed into the availableresource pool based on wait times or otherwise override defaultoperation.

FIG. 5 illustrates the processing of the handle requests component 330and/or 430, in one embodiment. The component is invoked to traverse thelist of requests and perform each request. In block 510, the componentretrieves the first request from the list. In block 520, the componentdispatches the request. Those of ordinary skill in the art willrecognize that dispatching a request may include many steps, such asretrieving media from a media library, loading the library in a diskdrive, gathering data from one or more computer systems, performing datamanagement operations on the data (e.g., compression, encryption,copying, etc.), and so forth. In decision block 530, the componentdetermines whether the requested resource has been blacklisted bycomparing the request to the generated blacklist table. If it is, thenthe routine proceeds in getting the next request in block 580 and loopsback to again dispatching the request in block 520.

If the requested resource is not blacklisted, then in block 535 acomponent performs one or more abbreviated checks, as described abovewith respect to FIG. 4. If the check fails, then the component continuesat block 540, else the component continues at block 545. In block 540,the component determines the category of the failed request and adds thecategory to a blacklist so that other requests that belong to thecategory will be flagged as likely to fail and thus not be dispatched bythe resource allocation system. In some embodiments the resourceallocation system first determines if the resource that caused therequest to fail is common (e.g., such that other similar resources arereadily available) or unique, and only blacklist the category if theresource is a unique resource.

In decision block 545, the component performs a full check, and if thatfails, the routine again loops back to adding the request to theblacklist category (block 540), getting the next request (block 580),and dispatching the request (block 520). If the full check succeeds,then the resource request is granted in block 550.

In decision block 555, if the request released resources, then thecomponent continues at block 560, else the component continues at block570. In block 560, the component places the released resources in atemporary resource holding area for release after the entire list hasbeen traversed. This prevents lower priority requests at the end of thelist from grabbing resources that higher priority requests at thebeginning of the list are waiting for. In decision block 570, if thereare more requests in the list, then the component continues at block580, else the component continues at block 590. In block 580, thecomponent retrieves the next request from the list and loops to block520 to dispatch the request. Blocks 510-580 depict dispatching requestsserially (e.g., one after the other) in order to simplify theillustration of the operation of the resource allocation system. Thoseof ordinary skill in the art will recognize that in practice manyrequests can be performed in parallel. In block 590, the component hasreached the end of the list and releases any temporarily held resourcesinto a global resource pool for access by any request. The componentthen loops to block 510 to traverse the list again. Typically theresource allocation system will loop repeatedly performing each requestremaining in the list until either the list of requests is exhausted orthe end of the storage operation window is reached. For example, thesystem may stop performing requests at the end of a nightly storagewindow.

Dynamic Routing/Allocation

Often resources are far flung geographically and throughout a network.For example, a company may have multiple offices each with their own LANand data management resources. The company may want to perform periodicdata management operations at each of the offices. For example, thecompany may backup user workstations at every office on a weekly basis.

In some embodiments, the resource allocation system forms a set ofresources needed by requests in a grid, table or other fashion to matchup a set of resources that can best satisfy a request. For example,although any tape library accessible by a user workstation could be usedto satisfy a request to backup the user workstation, it is likelydesirable to use a tape library that is close to the user workstation(where close could include geographic or network proximity). Theresource allocation system may group the data management operationsbased on a created logical table or grid allocation criteria. Forexample, the criteria may specify different subsets of data that areimportant to a particular user of the system. For example, a bank maydivide data by branch location or other criteria, or a government officemay divide data by the level of security clearance needed to access thenetwork on which the data is originally stored.

In some embodiments, the grid indicates alternate data paths that theresource allocation system can use if a preferred resource fails or isunavailable. The data path may specify a particular network route, tapelibrary, media agent, or other hardware or software to use if that datapath is selected to satisfy a request. For example, if there is afailover or load issue during the completion of a request, then theresource allocation system can attempt to use one of the alternate datapaths. The resource allocation system may determine if all of theelements of a particular data path are available before choosing thealternate data path.

In some embodiments, the resource allocation system receives rules thatspecify how alternate data paths are chosen. For example, an overflowrule may specify that when a particular data path or hardware resourceis full, requests for the data path should failover to a secondspecified data path. Alternatively or additionally, a rule may specifythat the resource allocation system should select data paths in analternating or round robin fashion to spread the load of requests evenlyacross data paths, or among lesser used resources to evenly spread wearout among all components.

FIG. 6 is a flow diagram that illustrates the processing of the buildgrid component 360, in one embodiment. In block 610, the componentreceives an initial request plan as described above. In block 620, thecomponent determines the grid dimensions. For example, the component maygroup the resources in columns according to common characteristics ofthe resources, such as geographic proximity, network topology,departments within an organization, and so forth. Then, rows of requestsmay be assigned to each column. In block 630, the component assignsrequests to the appropriate cell within the grid. For each request, thecomponent may assign the request based on the resources required by therequest or other configured criteria. The component may also determinean alternate set of resources for a request to be used when a first setof resources is not available. The methods described above foroptimizing the allocation of requests to resources may be used tooptimize the entire grid or columns of resources within the grid. Inblock 640, the component dispatches the requests within the grid. Eachcolumn of the grid may operate independently on separate lists ofrequests, and the component may process each list in parallel as well asperforming operations within each list in parallel.

Alternatively or additionally, the grid may include a row or column ofpriorities associated with each data management operation in a list ofdata management operations. The system may then perform data managementoperations along one dimension of the grid in priority order. Overall,the resource allocation system provides a highly scalable data storagesystem.

The resource allocation system can use the division of resources andrequests into a grid to further subdivide the problem of matchingrequests to resources. Within each dimension of the grid, the resourceallocation system may apply the techniques described above for reducingthe number of requests to be performed or the resources used forcompleting those requests. Thus, the grid store provides additionalscalability for performing data management operations.

FIG. 7 is a block diagram that illustrates an example environment inwhich the grid store may be applied. An organization may have threeoffices: Office A 710, Office B 740, and Office C 770. The offices areconnected by one or more networks, such as LAN 730 and WAN 760 (e.g.,the Internet). Each office has its own computer systems and data storagedevices (e.g., tape libraries, media agents, disk drives, and so forth).For example, Office A 710 has one or more user workstations 715 and 720and one or more data storage devices such as device 725, whereas OfficeB contains an E-Commerce server 745 (such as a website) and a databaseserver 750. Office B also has one or more data storage devices, such asdevice 755. Office C has an ERP system 775 and email sever 780 and oneor more data storage devices, such as device 785. Typically, it isdesirable to allow the data storage devices at each location handle thedata storage requests for that location. For example, the data storagedevice 725 is typically the preferred device for handling data storagerequests related to workstation 715. However, because each office isconnected by a network, it is also possible for data storage device 755to handle data storage requests related to workstation 715. The resourceallocation grid divides requests among the available resources, trackingthe types of preferences described. In addition, the resource allocationgrid may specify one or more alternate data paths to be used when thepreferred data path or data storage device is not available.

Overall, this system receives data storage requests to be performed in,e.g., multiple, geographically separated locations, wherein each of thelocations includes separate data storage resources. For each datastorage request, and before receiving data storage requests to beexecuted, the system determines at least two different sets of datastorage resources to handle the request. The first set of data storageresources is a preferred set of resources to handle the request, whilethe second set is an alternate set of data storage resources to handlethe request. Before receiving data storage requests to be executed, thesystem establishes a data storage resource allocation based at least inpart on one of the sets of data storage resources determined to handleeach data storage request.

Likewise, the system receives a list of multiple data managementresources for use in performing multiple data management operations andintelligently allocates those resources. For at least some of themultiple data management resources, the system determinescharacteristics of the data management resource (e.g. geographicproximity, network topology, departments within a business organization,type of hardware, etc.) and groups at least two of the resources basedon a similar characteristic. For each data management operation in thelist, the system then determines a location of one or more data objectsaffected by the data management operation, and creates a logical tablefor allocating the data management resources. This logical table forresource allocation selects one or more data management resources toperform each of the multiple data management operations in the list,based at least in part on the determined physical location of the one ormore data objects affected by the data management operation, and on thegrouping of at least two of the data management resources based on asimilarity of determined characteristics. Thereafter the system mayperform each data management operation based on the created logicaltable for resource allocation.

Conclusion

The resource allocation system described herein provides a tremendousamount of flexibility. It is applicable to heterogeneous networks andsystems, as well as systems that grow in size and diversity. Thus, adata management system with only a few localized cells may grow 10 or100 times larger with multiple geographically disbursed cells, withoutcompromising on backup windows and resource allocation times. Forexample, prior systems could accommodate 300 resource allocations in anhour, but under the present system, could handle over 40,000.

Systems and modules described herein may comprise software, firmware,hardware, or any combination(s) of software, firmware, or hardwaresuitable for the purposes described herein. Software and other modulesmay reside on servers, workstations, personal computers, computerizedtablets, PDAs, and other devices suitable for the purposes describedherein. In other words, the software and other modules described hereinmay be executed by a general-purpose computer, e.g., a server computer,wireless device or personal computer. Those skilled in the relevant artwill appreciate that aspects of the invention can be practiced withother communications, data processing, or computer systemconfigurations, including: Internet appliances, hand-held devices(including personal digital assistants (PDAs)), wearable computers, allmanner of cellular or mobile phones, multi-processor systems,microprocessor-based or programmable consumer electronics, set-topboxes, network PCs, mini-computers, mainframe computers, and the like.Indeed, the terms “computer,” “server,” “host,” “host system,” and thelike are generally used interchangeably herein, and refer to any of theabove devices and systems, as well as any data processor. Furthermore,aspects of the invention can be embodied in a special purpose computeror data processor that is specifically programmed, configured, orconstructed to perform one or more of the computer-executableinstructions explained in detail herein.

Software and other modules may be accessible via local memory, via anetwork, via a browser or other application in an ASP context, or viaother means suitable for the purposes described herein. Examples of thetechnology can also be practiced in distributed computing environmentswhere tasks or modules are performed by remote processing devices, whichare linked through a communications network, such as a Local AreaNetwork (LAN), Wide Area Network (WAN), or the Internet. In adistributed computing environment, program modules may be located inboth local and remote memory storage devices. Data structures describedherein may comprise computer files, variables, programming arrays,programming structures, or any electronic information storage schemes ormethods, or any combinations thereof, suitable for the purposesdescribed herein. User interface elements described herein may compriseelements from graphical user interfaces, command line interfaces, andother interfaces suitable for the purposes described herein. Screenshotspresented and described herein can be displayed differently as known inthe art to input, access, change, manipulate, modify, alter, and workwith information.

Examples of the technology may be stored or distributed oncomputer-readable media, including magnetically or optically readablecomputer discs, hard-wired or preprogrammed chips (e.g., EEPROMsemiconductor chips), nanotechnology memory, biological memory, or otherdata storage media. Indeed, computer implemented instructions, datastructures, screen displays, and other data under aspects of theinvention may be distributed over the Internet or over other networks(including wireless networks), on a propagated signal on a propagationmedium (e.g., an electromagnetic wave(s), a sound wave, etc.) over aperiod of time, or they may be provided on any analog or digital network(packet switched, circuit switched, or other scheme).

Unless the context clearly requires otherwise, throughout thedescription and the claims, the words “comprise,” “comprising,” and thelike are to be construed in an inclusive sense, as opposed to anexclusive or exhaustive sense; that is to say, in the sense of“including, but not limited to.” As used herein, the terms “connected,”“coupled,” or any variant thereof, means any connection or coupling,either direct or indirect, between two or more elements; the coupling ofconnection between the elements can be physical, logical, or acombination thereof. Additionally, the words “herein,” “above,” “below,”and words of similar import, when used in this application, shall referto this application as a whole and not to any particular portions ofthis application. Where the context permits, words in the above DetailedDescription using the singular or plural number may also include theplural or singular number respectively. The word “or,” in reference to alist of two or more items, covers all of the following interpretationsof the word: any of the items in the list, all of the items in the list,and any combination of the items in the list.

While certain aspects of the technology are presented below in certainclaim forms, the inventors contemplate the various aspects of thetechnology in any number of claim forms. For example, while only oneaspect of the technology is recited as a means-plus-function claim under35 U.S.C. §112, other aspects may likewise be embodied as ameans-plus-function claim. Accordingly, the inventors reserve the rightto add additional claims after filing the application to pursue suchadditional claim forms for other aspects of the technology.

The above detailed description of examples of the technology is notintended to be exhaustive or to limit the invention to the precise formdisclosed above. While specific embodiments of, and examples for, theinvention are described above for illustrative purposes, variousequivalent modifications are possible within the scope of the invention,as those skilled in the relevant art will recognize. For example, whileprocesses or blocks are presented in a given order, alternativeembodiments may perform routines having steps, or employ systems havingblocks, in a different order, and some processes or blocks may bedeleted, moved, added, subdivided, combined, and/or modified to providealternative or subcombinations. Each of these processes or blocks may beimplemented in a variety of different ways. Also, while processes orblocks are at times shown as being performed in series, these processesor blocks may instead be performed in parallel, or may be performed atdifferent times.

The teachings of the technology provided herein can be applied to othersystems, not necessarily the system described above. The elements andacts of the various embodiments described above can be combined toprovide further examples. Any patents and applications and otherreferences noted above, including any that may be listed in accompanyingfiling papers, are incorporated herein by reference. Aspects of theinvention can be modified, if necessary, to employ the systems,functions, and concepts of the various references described above toprovide yet further examples of the technology.

These and other changes can be made to the invention in light of theabove Detailed Description. While the above description describescertain embodiments of the invention, and describes the best modecontemplated, no matter how detailed the above appears in text, theinvention can be practiced in many ways. Details of the system andmethod for classifying and transferring information may varyconsiderably in its implementation details, while still beingencompassed by the invention disclosed herein. As noted above,particular terminology used when describing certain features or aspectsof the invention should not be taken to imply that the terminology isbeing redefined herein to be restricted to any specific characteristics,features, or aspects of the invention with which that terminology isassociated. In general, the terms used in the following claims shouldnot be construed to limit the invention to the specific embodimentsdisclosed in the specification, unless the above Detailed Descriptionsection explicitly defines such terms. Accordingly, the actual scope ofthe invention encompasses not only the disclosed embodiments, but alsoall equivalent ways of practicing or implementing the technology underthe claims. While certain aspects of the technology are presented belowin certain claim forms, the inventors contemplate the various aspects ofthe technology in any number of claim forms. For example, while only oneaspect of the technology is recited as embodied in a computer-readablemedium, other aspects may likewise be embodied in a computer-readablemedium. Accordingly, the inventors reserve the right to add additionalclaims after filing the application to pursue such additional claimforms for other aspects of the technology.

From the foregoing, it will be appreciated that specific embodiments ofthe invention have been described herein for purposes of illustration,but that various modifications may be made without deviating from thespirit and scope of the invention. Accordingly, the invention is notlimited except as by the appended claims.

We claim:
 1. A method for data storage resource allocation based onclassifying data storage requests, the method comprising: classifying,by a server in a data management system, data storage requests into aplurality of categories, wherein a category of a respective data storagerequest is based on a storage policy comprising rules for allocatingdata storage resources for the respective data storage request, andwherein the data storage requests are in a queue of data storagerequests to be performed in the data management system; determining, bythe server, based on one or more abbreviated checks, whether a firstdata storage request in the queue of data storage requests would fail ifattempted, wherein the determining comprises: (i) selecting, from aplurality of data storage resources required by the first data storagerequest, one or more data storage resources that are physical resources,and (ii) performing, in an order based on relative chances of failure ofthe respective selected physical resources and ahead of any logicalchecks of the selected physical resources, one or more physical checksof whether the selected physical resources are available for the firstdata storage request, wherein the performing of the one or more physicalchecks includes determining whether hardware for performing the firstdata storage request is working; and when the server determines that,based on the one or more abbreviated checks, the first data storagerequest would fail if attempted, updating the queue of data storagerequests, by the server, to indicate that: (a) the first data storagerequest and (b) one or more second data storage requests classified inthe same category as the first data storage request should not beperformed, wherein updating the queue occurs without checking whetherthe one or more second data storage requests would fail if attempted,and wherein updating the queue occurs without attempting to perform thefirst data storage request and the one or more second data storagerequests.
 2. The method of claim 1, wherein updating the queue enablesone or more third data storage requests to be performed before the firstdata storage request and the one or more second data storage requests,and wherein the one or more third data storage requests are associatedwith a category different from the category of the first data storagerequest and the one or more second data storage requests.
 3. The methodof claim 1, wherein a category of a given data storage request isfurther defined by data storage resource requirements that are similarto other data storage requests classified in the same category.
 4. Themethod of claim 1, wherein a category of a given data storage request isfurther defined by rules for data storage resource allocation that aresimilar to other data storage requests classified in the same category.5. The method of claim 1 further comprising: if the first data storagerequest fails in the course of being performed, further updating thequeue to indicate that the one or more second data storage requestsclassified in the same category as the first data storage request shouldnot be performed, wherein the further updating of the queue occurswithout checking to determine whether the one or more second datastorage requests would fail if attempted, and wherein the furtherupdating of the queue occurs without attempting to perform the one ormore second data storage requests.
 6. The method of claim 1, wherein thequeue of data storage requests is initially ordered into an order ofpriority for performing the data storage requests; and wherein updatingthe queue removes the first data storage request and the one or moresecond data storage requests from the queue, thereby changing the orderof priority.
 7. The method of claim 1, wherein by updating the queue,the server thereby defers performing the first data storage request andthe one or more second data storage requests.
 8. A data managementsystem for data storage resource allocation based on classifying datastorage requests, the system comprising: a server hosting a storagemanager comprising a database, wherein the database comprises storagepolicies that govern how to allocate resources for data storagerequests; and wherein the storage manager is configured to: maintain aqueue of data storage requests to be performed in the data managementsystem, classify data storage requests into a plurality of categories,wherein a category of a given data storage request is associated with astorage policy that governs how to allocate resources for the given datastorage request, and determine based on one or more abbreviated checks,whether a first data storage request in the queue of data storagerequests would fail if attempted, comprising: (i) selecting physicalresources required by the first data storage request, and (ii)performing, in an order based on relative chances of failure of therespective selected storage resources and ahead of checking any logicalresources required by the first data storage request, one or more checksof whether the selected physical resources are available for the firstdata storage request, including whether hardware for performing thefirst data storage request is working; and when the server determines,based on the one or more abbreviated checks, that the first data storagerequest would fail if attempted, updating the queue of data storagerequests to indicate that: (a) the first data storage request and (b)one or more second data storage requests classified in the same categoryas the first data storage request should not be performed, wherein theserver updates the queue without checking whether the one or more seconddata storage requests would fail if attempted, and wherein the serverupdates the queue without attempting to perform the first data storagerequest and the one or more second data storage requests.
 9. The datamanagement system of claim 8, wherein after the queue is updated one ormore third data storage requests are performed before the first datastorage request and the one or more second data storage requests, andwherein the one or more third data storage requests are associated witha category different from the category of the first data storage requestand the one or more second data storage requests.
 10. The datamanagement system of claim 8, wherein a category of a given data storagerequest is further defined by data storage resource requirements thatare similar to other data storage requests classified in the samecategory.
 11. The data management system of claim 8, wherein a categoryof a given data storage request is further defined by rules for datastorage resource allocation that are similar to other data storagerequests classified in the same category.
 12. The data management systemof claim 8, wherein the server is further configured to: if the firstdata storage request fails in the course of being performed, furtherupdate the queue to indicate that the one or more second data storagerequests classified in the same category as the first data storagerequest should not be performed, wherein the server further updates thequeue without checking to determine whether the one or more second datastorage requests would fail if attempted, and wherein the server furtherupdates the queue without attempting to perform the one or more seconddata storage requests.
 13. The data management system of claim 8,wherein by updating the queue, the server thereby defers performing thefirst data storage request and the one or more second data storagerequests.
 14. A computer-readable medium, excluding transitorypropagating signals, storing instructions that, when executed by aserver in a data management system, cause the server to perform a methodcomprising: (i) in reference to a queue of data storage requests to beperformed in the data management system, wherein each data storagerequest is governed by a policy that governs one or more data storagerequests, and wherein each data storage request requires data storageresources based on criteria in the respective policy, classifying eachdata storage request into one of a plurality of categories, wherein agiven category is defined by at least one of (a) similar requirementsfor one or more data storage resources and (b) similar criteria in arespective governing policy, (ii) determining whether a first datastorage request in the queue of data storage requests would fail ifattempted, based on abbreviated resource checking comprising: (a)identifying which of the data storage resources in a respectiveplurality of data storage resources needed to perform the first datastorage request are physical resources and which ones are logicalresources, (b) checking whether the identified physical resources areavailable for the first data storage request before attempting to checkany of the logical resources, and (c) if the checking of the identifiedphysical resources indicate that the physical resources would not causethe first data storage request to fail if attempted, checking whetherthe identified logical resources are available for the first datastorage request, (iii) when determining that the first data storagerequest would fail if attempted, based on the abbreviated resourcechecking, removing from the queue of data storage requests: (I) thefirst data storage request and (II) one or more second data storagerequests classified in the same category as the first data storagerequest, (A) without attempting any abbreviated resource checks todetermine whether the one or more second data storage requests wouldfail if attempted, and (B) without attempting to perform the first datastorage request and the one or more second data storage requests; andwherein the classifying of each data storage request into one of aplurality of categories occurs before determining based on abbreviatedresource checking whether any data storage request in the queue,including the first data storage request, would fail if attempted. 15.The computer-readable medium of claim 14, wherein the method furthercomprises: if the first data storage request fails while beingperformed, removing from the queue of data storage requests the one ormore second data storage requests classified in the same category as thefirst data storage request, without checking to determine whether theone or more second data storage requests would fail if attempted, andwithout attempting to perform the one or more second data storagerequests.
 16. The computer-readable medium of claim 14, wherein theremoved data storage requests are deferred to another time.
 17. Thecomputer-readable medium of claim 14, wherein the server composes alikeness factor for determining when the at least one of (a) similarrequirements for one or more data storage resources and (b) similarcriteria in a respective governing policy are sufficiently similar forclassifying two or more data storage requests in the same category. 18.The computer-readable medium of claim 14, wherein the server composes alikeness factor, based on two or more common data storage resources, fordetermining when the at least one of (a) similar requirements for one ormore data storage resources and (b) similar criteria in a respectivegoverning policy.